1. Field of the Invention
This invention relates generally to semiconductor manufacturing, and, more particularly, to a method and apparatus for performing an adaptive state estimation process based upon manufacturing data to reduce process variation.
2. Description of the Related Art
The technology explosion in the manufacturing industry has resulted in many new and innovative manufacturing processes. Today's manufacturing processes, particularly semiconductor manufacturing processes, call for a large number of important steps. These process steps are usually vital, and therefore, require a number of inputs that are generally fine-tuned to maintain proper manufacturing control.
The manufacture of semiconductor devices requires a number of discrete process steps to create a packaged semiconductor device from raw semiconductor material. The various processes, from the initial growth of the semiconductor material, the slicing of the semiconductor crystal into individual wafers, the fabrication stages (etching, doping, ion implanting, or the like), to the packaging and final testing of the completed device, are so different from one another and specialized that the processes may be performed in different manufacturing locations that contain different control schemes.
Generally, a set of processing steps is performed across a group of semiconductor wafers, sometimes referred to as a lot. For example, a process layer that may be composed of a variety of different materials may be formed across a semiconductor wafer. Thereafter, a patterned layer of photoresist may be formed across the process layer using known photolithography techniques. Typically, an etch process is then performed across the process layer using a patterned layer of photoresist as a mask. This etching process results in the formation of various features or objects in the process layer. Such features may be used as, for example, a gate electrode structure for transistors. Many times, trench isolation structures are also formed across the substrate of the semiconductor wafer to isolate electrical areas across a semiconductor wafer. One example of an isolation structure that can be used is a shallow trench isolation (STI) structure.
The manufacturing tools within a semiconductor manufacturing facility typically communicate with a manufacturing framework or a network of processing modules. Each manufacturing tool is generally connected to an equipment interface. The equipment interface is connected to a machine interface to which a manufacturing network is connected, thereby facilitating communications between the manufacturing tool and the manufacturing framework. The machine interface can generally be part of an advanced process control (APC) system. The APC system initiates a control script, which can be a software program that automatically retrieves the data needed to execute a specific manufacturing process.
FIG. 1 illustrates a typical semiconductor wafer 105. The semiconductor wafer 105 typically includes a plurality of individual semiconductor die 103 arranged in a grid 150. Using known photolithography processes and equipment, a patterned layer of photoresist may be formed across one or more process layers that are to be patterned. As part of the photolithography process, an exposure process is typically performed by a stepper on single or multiple die 103 locations at a time, depending on the specific photomask employed. The patterned photoresist layer can be used as a mask during etching processes, wet or dry, performed on the underlying layer or layers of material, e.g., a layer of polysilicon, metal or insulating material, to transfer the desired pattern to the underlying layer. The patterned layer of photoresist is comprised of a plurality of features, e.g., line-type features or opening-type features that are to be replicated in an underlying process layer.
State-of-the-art processing systems utilize a state estimation function in order to determine process control parameters. State estimation functions may include an evaluation of the performance of a controller that controls a process function. Generally, state estimation functions are performed upon processing wafers and acquiring metrology data relating to the processed wafers.
Turning now to FIG. 2, a flowchart depiction of a prior art process flow is illustrated. A manufacturing system may process a batch of semiconductor wafers (block 210). Upon processing the wafers, metrology data related to at least some of the processed wafers may be acquired (block 220). Based upon the metrology data, a state estimation function may be performed by the manufacturing system (block 230). The state estimation function may relate to an evaluation of the performance of the controller related to the manufacturing system. Based upon the estate estimation process, the manufacturing system may adjust various parameters of the controller (e.g., a run-to-run controller) for controlling the process operation of subsequent semiconductor wafers (block 240).
One problem associated with the state-of-the-art methodology includes the fact that generally, different sets of metrology data are processed and treated in the same manner even though they may have different characteristics. An example of a state estimator may be an EWMA estimator. The state-of-the-art generally uses the EWMA estimator in such a manner that substantially equal weight is applied to all incoming data that is used to determine the current state estimate of a process system. Generally, state-of-the-art state estimation functions provide a state estimation based upon substantially equal weight applied to the metrology data regardless of any special properties associated with a particular set of metrology data. This may lead to an erroneous assessment of the operation of the controller.
In the state-of-the-art, the underlying information associated with a particular group of metrology data sets may be considered. Therefore, metrology data that is substantially more representative of actual conditions may not be adequately represented in the group of data sets that may be used to perform a state estimation. For example, the goodness-of-fit value associated with the metrology data that is above a predetermined threshold may be all treated equally. For example, if a threshold of 0.7 goodness-of-fit factor value is used as a threshold, the controller may provide equal weight to a goodness-of-fit result of 0.75 as to a goodness-of-fit result of 0.95. These technicalities may cause feedback or feed-forward corrections that are not adequately accurate, thereby, causing further reduction in quality or yield relating to processed semiconductor wafers 105.
The present invention is directed to overcoming, or at least reducing, the effects of one or more of the problems set forth above.